Unimodal density estimation using kernel methods
We suggest a method for rendering a standard kernel density estimator unimodal: tilting the empirical distribution. It is proposed that the amount of tilting be chosen in order to minimise, subject to unimodality, the integrated squared distance between a conventional density estimator and its tilted version. This approach has an interesting data-compression aspect, in that the algorithm often implicitly summarises the dataset in a relatively small subsample as part of the process of enforcing...[Show more]
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